Search results for: product feature extraction

Authors: Mustapha Mahmoud Dif, Fouzia Benali-Toumi, Mohamed Benyahia, Sofiane Bouazza, Abbes Dellal, Slimane Baha

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L. multifida is applied to treat rheumatism and cold and has hypoglycemic and anti-inflammatory properties. The present study is to optimize the extraction of phenolic compounds in Algerian Lavandula multifida. The influences of parameters including temperature (decoction and maceration) and extraction time (15min to 45 min) on the flavonoids concentration are studied. The optimal conditions are determined and the quadratic response surfaces draw from the mathematical models. Total phenols were evaluated using Folin sicaltieu methods, total flavonoids were estimated using the Tri chloral aluminum method. The maximum concentration extracted, for total flavonoids, equal to 0.043 mg/g was achieved with decoction and extraction time of 41.55 min. However, for total phenol compounds highest concentration of 0.218 mg/g, is obtained with 45 min at 49.99°C.

Keywords: L multifidi, phenolic content, optimization, time, temperature

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Authors: Atcharawan Phenwansuk

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The product design is important to the development of SME towards the global, because it made to the quality product to react the needs of consumers and could reduces cost in the production, making it more profitable. As a results, the business are competition advantage for more marketing. It also enhance image of product and firms to build its own brand products to be acceptable. The product was designed should be shape, size, colorful, and direct of target consumers. This is method to add value products to get popular and effective, because the beauty is first satisfaction which come from main shape and color of the design product, but the product was designed need to hold data and law combination of shape and color between artistic theory and satisfaction of consumers together. The design must consider the safety of life and asset of consumers the most important. From to use of designed products should be to consider the cost savings, convenient distance, transportation, routes (land, water or air) of living space on transport (capacity, volume, width, length of the car, truck and container, etc). The packaging must be can to prevent not damage of the products. If products is more large , maybe to design new packaging, which can easily disassembled for make smaller package such as designing the assembly. Products must be packed in the container for size standard for save costs, as well as the buyer can make transport and assembly of products to fit easily on your own.

Keywords: logistics process , pineapple’s leaves product, product design, satisfaction of consumers

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Authors: K. P. Sandesh, M. H. Suman

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Text processing plays an important role in information retrieval, data-mining, and web search. Measuring the similarity between the documents is an important operation in the text processing field. In this project, a new similarity measure is proposed. To compute the similarity between two documents with respect to a feature the proposed measure takes the following three cases into account: (1) The feature appears in both documents; (2) The feature appears in only one document and; (3) The feature appears in none of the documents. The proposed measure is extended to gauge the similarity between two sets of documents. The effectiveness of our measure is evaluated on several real-world data sets for text classification and clustering problems, especially in banking and health sectors. The results show that the performance obtained by the proposed measure is better than that achieved by the other measures.

Keywords: document classification, document clustering, entropy, accuracy, classifiers, clustering algorithms

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Authors: Amarjit Singh

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In this paper, a method for extraction of text subtitles in large video is proposed. The video data needs to be annotated for many multimedia applications. Text is incorporated in digital video for the motive of providing useful information about that video. So need arises to detect text present in video to understanding and video indexing. This is achieved in two steps. First step is text localization and the second step is text verification. The method of text detection can be extended to text recognition which finds applications in automatic video indexing; video annotation and content based video retrieval. The method has been tested on various types of videos.

Keywords: video, subtitles, extraction, annotation, frames

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Authors: Jihan Abdulazeez Ahmed, Adnan Mohsin Abdulazeez Brifcani

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This paper suggests a new internal architecture of holon based on feature selection model using the combination of Bees Algorithm (BA) and Artificial Neural Network (ANN). BA is used to generate features while ANN is used as a classifier to evaluate the produced features. Proposed system is applied on the Wine data set, the statistical result proves that the proposed system is effective and has the ability to choose informative features with high accuracy.

Keywords: artificial neural network, bees algorithm, feature selection, Holon

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Authors: Gargi Phadke, Mugdha Joshi, Shamal Salunkhe

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Facial sketches are used as a crucial clue by criminal investigators for identification of suspects when the description of eyewitness or victims are only available as evidence. A forensic artist develops a sketch as per the verbal description is given by an eyewitness that shows the facial look of the culprit. In this paper, the fusion of Scale Invariant Feature Transform (SIFT) and multiscale local binary patterns (MLBP) are proposed as a feature to recognize a forensic face sketch images from a gallery of mugshot photos. This work focuses on comparative analysis of proposed scheme with existing algorithms in different challenges like illumination change and rotation condition. Experimental results show that proposed scheme can lead to better performance for the defined problem.

Keywords: SIFT feature, MLBP, PCA, face sketch

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Authors: Jone Ibarruri, Mikel Manso, Marta Cebrián

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A high amount of food is lost or discarded in the World every year. In addition, in the last decades, an increasing demand of new alternative and sustainable sources of proteins and other valuable compounds is being observed in the food and feeding sectors and, therefore, the use of food by-products as nutrients for these purposes sounds very interesting from the environmental and economical point of view. However, the direct use of discarded fruit and vegetables that present, in general, a low protein content is not interesting as feeding ingredient except if they are used as a source of fiber for ruminants. Especially in the case of aquaculture, several alternatives to the use of fish meal and other vegetable protein sources have been extensively explored due to the scarcity of fish stocks and the unsustainability of fishing for these purposes. Fish mortality is also of great concern in this sector as this problem highly reduces their economic feasibility. So, the development of new functional and natural ingredients that could reduce the need for vaccination is also of great interest. In this work, several fermentation tests were developed at lab scale using a selected mixture of fruit and vegetable discards from a wholesale market located in the Basque Country to increase their protein content and also to produce some bioactive extracts that could be used as additives in aquaculture. Fruit and vegetable mixtures (60/40 ww) were centrifugated for humidity reduction and crushed to 2-5 mm particle size. Samples were inoculated with a selected Rhizopus oryzae strain and fermented for 7 days in controlled conditions (humidity between 65 and 75% and 28ºC) in Petri plates (120 mm) by triplicate. Obtained results indicated that the final fermented product presented a twofold protein content (from 13 to 28% d.w). Fermented product was further processed to determine their possible functionality as a feed additive. Extraction tests were carried out to obtain an ethanolic extract (60:40 ethanol: water, v.v) and remaining biomass that also could present applications in food or feed sectors. The extract presented a polyphenol content of about 27 mg GAE/gr d.w with antioxidant activity of 8.4 mg TEAC/g d.w. Remining biomass is mainly composed of fiber (51%), protein (24%) and fat (10%). Extracts also presented antibacterial activity according to the results obtained in Agar Diffusion and to the Minimum Inhibitory Concentration (MIC) tests determined against several food and fish pathogen strains. In vitro, digestibility was also assessed to obtain preliminary information about the expected effect of extraction procedure on fermented product digestibility. First results indicated that remaining biomass after extraction doesn´t seem to improve digestibility in comparison to the initial fermented product. These preliminary results show that fermented fruit and vegetables can be a useful source of functional ingredients for aquaculture applications and a substitute of other protein sources in the feeding sector. Further validation will be also carried out through “in vivo” tests with trout and bass.

Keywords: fungal solid state fermentation, protein increase, functional extracts, feed ingredients

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Authors: Tamanna Goyal, Divya Bansal, Sanjeev Sofat

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In world-threatening terrorist attacks, where early detection, distinction, and prediction are effective diagnosis techniques and for functionally accurate and precise analysis of terrorism data, there are so many data mining & statistical approaches to assure accuracy. The computational extraction of derived patterns is a non-trivial task which comprises specific domain discovery by means of sophisticated algorithm design and analysis. This paper proposes an approach for similarity extraction by obtaining the useful attributes from the available datasets of terrorist attacks and then applying feature selection technique based on the statistical impurity measures followed by clustering techniques on the basis of similarity measures. On the basis of degree of participation of attributes in the rules, the associative dependencies between the attacks are analyzed. Consequently, to compute the similarity among the discovered rules, we applied a weighted similarity measure. Finally, the rules are grouped by applying using hierarchical clustering. We have applied it to an open source dataset to determine the usability and efficiency of our technique, and a literature search is also accomplished to support the efficiency and accuracy of our results.

Keywords: association rules, clustering, similarity measure, statistical approaches

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Authors: Nougrara Zineb

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The unique structure of the blood vessels in the retina has been used for biometric identification. The retina blood vessel pattern is a unique pattern in each individual and it is almost impossible to forge that pattern in a false individual. The retina biometrics’ advantages include high distinctiveness, universality, and stability overtime of the blood vessel pattern. Once the creases have been extracted from the images, a registration stage is necessary, since the position of the retinal vessel structure could change between acquisitions due to the movements of the eye. Image registration consists of following steps: Feature detection, feature matching, transform model estimation and image resembling and transformation. In this paper, we present an algorithm of registration; it is based on the characterization of retinal feature points. For experiments, retinal images from the DRIVE database have been tested. The proposed methodology achieves good results for registration in general.

Keywords: fovea, optic disc, registration, retinal images

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Authors: Hala Zaghloul, Taymoor Nazmy

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One of the great challenges of the 21st century is to build a robot that can perceive and act within its environment and communicate with people, while also exhibiting the cognitive capabilities that lead to performance like that of people. The Pulse Coupled Neural Network, PCNN, is a relative new ANN model that derived from a neural mammal model with a great potential in the area of image processing as well as target recognition, feature extraction, speech recognition, combinatorial optimization, compressed encoding. PCNN has unique feature among other types of neural network, which make it a candid to be an important approach for perceiving in cognitive systems. This work show and emphasis on the potentials of PCNN to perform different tasks related to image processing. The main drawback or the obstacle that prevent the direct implementation of such technique, is the need to find away to control the PCNN parameters toward perform a specific task. This paper will evaluate the performance of PCNN standard model for processing images with different properties, and select the important parameters that give a significant result, also, the approaches towards find a way for the adaptation of the PCNN parameters to perform a specific task.

Keywords: cognitive system, image processing, segmentation, PCNN kernels

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Authors: G. Schuh, S. Woelk, D. Schraknepper, A. Such

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The systematic evaluation of manufacturing technologies with regard to the potential for product designing constitutes a major challenge. Until now, conventional evaluation methods primarily consider the costs of manufacturing technologies. Thus, the potential of manufacturing technologies for achieving additional product design features is not completely captured. To compensate this deficit, final evaluations of new technologies are mainly intuitive in practice. Therefore, an additional evaluation dimension is needed which takes the potential of manufacturing technologies for specific realizable product designs into account. In this paper, we present the approach of an evaluation method for selecting manufacturing technologies with regard to their potential for product designing. This research is done within the Fraunhofer innovation cluster »AdaM« (Adaptive Manufacturing) which targets the development of resource efficient and adaptive manufacturing technology processes for complex turbo machinery components.

Keywords: manufacturing, product design, production, technology assessment, technology management

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Authors: Heungwook Son, Sungjoo Lee

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Recently, due to intensifying competition in several industries, the importance of meeting customer requirements has increased. The role that service plays in satisfying customer‘s requirements is key area of focus. Thus, the concept of using product development-research in the service system has been actively practiced. As strategic decision making tool, various types of the technology roadmap were suggested in the product-service system (PSS). However, the technology roadmap was configured a top-down form around the technologies of the elements. The limitation is that it hard for it to indicate a variety of interrelations. In response, this paper suggests using the planning support tool of PSS for a DSM for the technology roadmap; it consists of the relationship of product-service-technology as a bottom-up form. Therefore, nine types of the technology roadmap of PSS exist. The first defines the relationship of product-service-technology. The second phase identifies output when of the technology roadmaps are adapted to the DSM process. Finally, the DSM-based forms of each type of technology roadmap are presented through case studies.

Keywords: DSM, technology roadmap, PSS, product-service system, bottom-up

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Authors: Kimia Kiaei, Mohammad Hasan Golpayegani

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The extraction of copper from a pregnant leach solution obtained through leaching was investigated in this study. Chemorex CP-150 was utilized as an organic extractant, while kerosene served as a diluent. The study focused on determining the optimal ratios of extractant to diluent, as well as the pH of the aqueous phase. Isotherm curves of extraction were generated, and Mc. Cabe-Thiele diagrams were constructed separately for an optimized experimental pH of 3.17 and a typical industrial pH of 2. Additionally, the sulfuric acid-to-PLS ratio and concentrations of interfering ions comprising Mn²⁺ and Fe³⁺ in the strip solution were evaluated during the stripping stage. The results indicated that the optimized values for the extractant-to-diluent ratio and pH were 5% and 3.17, respectively. The Mc. Cabe-Thiele diagrams revealed that at an aqueous-to-organic ratio of 1, the theoretical stages of solvent extraction at pH levels of 3.17 and 2 were one and two, respectively. Moreover, a sulfuric acid-to-PLS ratio of 20% was employed in the stripping stage, and it was observed that the concentrations of interfering ions fell within the acceptable range.

Keywords: copper, solvent extraction, heap leaching, Chemorex CP-150, pregnant leach solution

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Authors: Seyedeh Bahar Hashemi, Alireza Rahimi, Mehdi Arjmand

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Food is the source of energy and growth through the breakdown of its vital components and plays a vital role in human health and nutrition. Many natural compounds found in plant and animal materials play a special role in biological systems and the origin of many such compounds directly or indirectly is algae. Algae is an enormous source of polysaccharides and have gained much interest in human flourishing. In this study, algae biomass extraction is conducted using deep eutectic-based solvents (NADES) and Ultrasound-assisted extraction (UAE). The aim of this research is to extract bioactive compounds including total carotenoid, antioxidant activity, and polyphenolic contents. For this purpose, the influence of three important extraction parameters namely, biomass-to-solvent ratio, temperature, and time are studied with respect to their impact on the recovery of carotenoids, and phenolics, and on the extracts’ antioxidant activity. Here we employ the Response Surface Methodology for the process optimization. The influence of the independent parameters on each dependent is determined through Analysis of Variance. Our results show that Ultrasound-assisted extraction (UAE) for 50 min is the best extraction condition, and proline:lactic acid (1:1) and choline chloride:urea (1:2) extracts show the highest total phenolic contents (50.00 ± 0.70 mgGAE/gdw) and antioxidant activity [60.00 ± 1.70 mgTE/gdw, 70.00 ± 0.90 mgTE/gdw in 2.2-diphenyl-1-picrylhydrazyl (DPPH), and 2.2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS)]. Our results confirm that the combination of UAE and NADES provides an excellent alternative to organic solvents for sustainable and green extraction and has huge potential for use in industrial applications involving the extraction of bioactive compounds from algae. This study is among the first attempts to optimize the effects of ultrasonic-assisted extraction, ultrasonic devices, and deep natural eutectic point and investigate their application in bioactive compounds extraction from algae. We also study the future perspective of ultrasound technology which helps to understand the complex mechanism of ultrasonic-assisted extraction and further guide its application in algae.

Keywords: natural deep eutectic solvents, ultrasound-assisted extraction, algae, antioxidant activity, phenolic compounds, carotenoids

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Authors: Spandana Ramisetty, Mandan Chidambaram, Ramesh Bhujade

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Algal biomass is not only a potential source for biocrude but also for high value chemicals like carotenoids, fatty acids, proteins, polysaccharides, vitamins etc. Astaxanthin is one such high value vital carotenoid which has extensive applications in pharmaceutical, aquaculture, poultry and cosmetic industries and expanding as dietary supplement to humans. Green microalgae Haematococcus pluvialis is identified as the richest natural source of astaxanthin and is the key source of commercial astaxanthin. Several extraction processes from wet and dry Haematococcus pluvialis biomass have been explored by researchers. Extraction with supercritical CO₂ and various physical disruption techniques like mortar and pestle, homogenization, ultrasonication and ball mill from dried algae are widely used extraction methods. However, these processes require energy intensive drying of biomass that escalates overall costs notably. From the process economics perspective, it is vital to utilize wet processing technology in order to eliminate drying costs. Hydrothermal liquefaction (HTL) is a thermo-chemical conversion process that converts wet biomass containing over 80% water to bio-products under high temperature and high pressure conditions. Astaxanthin is a lipid soluble pigment and is usually extracted along with lipid component. Mild HTL at 200°C and 60 bar has been demonstrated by researchers in a microfluidic platform achieving near complete extraction of astaxanthin from wet biomass. There is very limited work done in this field. An integrated approach of sequential HTL offers cost-effective option to extract astaxanthin/lipid from wet algal biomass without drying algae and also recovering water, minerals and nutrients. This paper reviews past work and evaluates the astaxanthin extraction processes with focus on hydrothermal extraction.

Keywords: astaxanthin, extraction, high value chemicals, hydrothermal liquefaction

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Authors: Bubai Maji, Monorama Swain

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Speech is considered an essential and most natural medium for the interaction between machines and humans. However, extracting effective features for speech emotion recognition (SER) is remains challenging. The present studies show that the temporal information captured but high-level temporal-feature learning is yet to be investigated. In this paper, we present an efficient novel method using the Self-attention (SA) mechanism in a combination of Convolutional Neural Network (CNN) and Bi-directional Gated Recurrent Unit (Bi-GRU) network to learn high-level temporal-feature. In order to further enhance the representation of the high-level temporal-feature, we integrate a Bi-GRU output with learnable weights features by SA, and improve the performance. We evaluate our proposed method on our created SITB-OSED and IEMOCAP databases. We report that the experimental results of our proposed method achieve state-of-the-art performance on both databases.

Keywords: Bi-GRU, 1D-CNNs, self-attention, speech emotion recognition

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Authors: Jiawen Wang, Qijun Chen

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The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

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Authors: Ezeni Brzovska, Durdana Ozretic-Dosen

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The purpose of this paper is to deepen the understanding of the product cues that influence purchase decision for a specific product category – chocolate, and to identify demographic differences in the buying behavior. ANOVA was employed for analyzing the significance level for nine product cues, and the survey showed statistically significant differences among different age and gender groups, and between respondents with different levels of education. From the theoretical perspective, the study adds to the existing knowledge by contributing with the research results from the new environment (Southeast Europe, Macedonia), which has been neglected so far. Establishing the level of significance for the product cues that affect buying behavior in the chocolate consumption context might help managers to improve marketing decision-making, and better meet consumer needs through identifying opportunities for packaging innovations and/or personalization toward different target groups.

Keywords: chocolate consumption context, chocolate selection, demographic characteristics, product cues

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Authors: Naser Safdarian, Nader Jafarnia Dabanloo

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In this paper we used four features i.e. Q-wave integral, QRS complex integral, T-wave integral and total integral as extracted feature from normal and patient ECG signals to detection and localization of myocardial infarction (MI) in left ventricle of heart. In our research we focused on detection and localization of MI in standard ECG. We use the Q-wave integral and T-wave integral because this feature is important impression in detection of MI. We used some pattern recognition method such as Artificial Neural Network (ANN) to detect and localize the MI. Because these methods have good accuracy for classification of normal and abnormal signals. We used one type of Radial Basis Function (RBF) that called Probabilistic Neural Network (PNN) because of its nonlinearity property, and used other classifier such as k-Nearest Neighbors (KNN), Multilayer Perceptron (MLP) and Naive Bayes Classification. We used PhysioNet database as our training and test data. We reached over 80% for accuracy in test data for localization and over 95% for detection of MI. Main advantages of our method are simplicity and its good accuracy. Also we can improve accuracy of classification by adding more features in this method. A simple method based on using only four features which extracted from standard ECG is presented which has good accuracy in MI localization.

Keywords: ECG signal processing, myocardial infarction, features extraction, pattern recognition

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Authors: Natália C. C. Lobato, Ângela M. Ferreira, Marcelo B. Mansur

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In solvent extraction operations, large sedimentation areas in the mixer-settler are required when the disengagement of the aqueous and the organic phases is slow and/or difficult. The use of a magnetic organic liquid (also known as ferrofluid), consisting of magnetite nanoparticles coated by oleic acid dispersed in the organic diluent, has proven successful to speed up phase disengagement. The method, however, has never been used industrially; therefore, the aim of this study is to raise its main limitations. Tests were carried out using a ferrofluid containing 30 g/l of magnetite dissolved in commercial aliphatic kerosene Exxsol D80. The efficiency of cobalt extraction ([Co] = 1 g/l) with 10% v/v Cyanex 272 (bis-2,4,4-trimethylpentyl phosphinic acid) at changing pH of the aqueous phase (2 to 7) was found unaffected in the conditions studied. However, the chemical resistance of the ferrofluid in contact with deionized water at changing acidity (from 10-7 to 2 mol/l) revealed that the nanoparticles are not resistant when contacted to aqueous solutions with a pH ≤ 2. Such result represents a serious limitation to the applicability of the method mainly to hydrometallurgical systems because solvent extraction operations are normally done in acid conditions, therefore more effective strategies to coat the particles are required.

Keywords: magnetic solvent extraction, oleic acid, magnetite nanoparticles, cyanex 272

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Authors: Shashikant R. Kuchekar, Somnath D. Bhumkar, Haribhau R. Aher, Bhaskar H. Zaware, Ponnadurai Ramasami

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A precise, sensitive, rapid and selective method for the solvent extraction, spectrophotometric determination of palladium(II) using para-methylphenyl thiourea (PMPT) as an extractant is developed. Palladium(II) forms yellow colored complex with PMPT which shows an absorption maximum at 300 nm. The colored complex obeys Beer’s law up to 7.0 µg ml^-1 of palladium. The molar absorptivity and Sandell’s sensitivity were found to be 8.486 x 10³ l mol^-1cm^-1 and 0.0125 μg cm^-2 respectively. The optimum conditions for the extraction and determination of palladium have been established by monitoring the various experimental parameters. The precision of the method has been evaluated and the relative standard deviation has been found to be less than 0.53%. The proposed method is free from interference from large number of foreign ions. The method has been successfully applied for the determination of palladium from alloy, synthetic mixtures corresponding to alloy samples.

Keywords: solvent extraction, PMPT, Palladium (II), spectrophotometry

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Authors: Yingxin Hui

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Understanding seismic response feature of the bridges crossing fault is the basis of the seismic fortification. Taking a multi-span bridge crossing active fault under construction as an example, the seismic ground motions at bridge site were generated following hybrid simulation methodology. Multi-support excitations displacement input models and nonlinear time history analysis was used to calculate seismic response of structures, and the results were compared with bridge in the near-fault region. The results showed that the seismic response features of bridges crossing fault were different from the bridges in the near-fault region. The design according to the bridge in near-fault region would cause the calculation results with insecurity and non-reasonable if the effect of cross the fault was ignored. The design of seismic fortification should be based on seismic response feature, which could reduce the adverse effect caused by the structure damage.

Keywords: bridge engineering, seismic response feature, across faults, rupture directivity effect, fling step

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Authors: Boy Arief Fachri

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Even its content is rich in antioxidants ϒ-oryzanol, rice bran is not used properly as functional food. This research aims to (1) extract ϒ-oryzanol; (2) determine the solubility of ϒ-oryzanol in supercritical CO₂ based on phase equilibrium theory; and (3) study the effect of process variables on solubility. Extraction experiments were carried out for rice bran (5 g) at various extraction pressures, temperatures and reaction times. The flowrate of supercritical fluid through the extraction vessel was 25 g/min. The extracts were collected and analysed with high-pressure liquid chromatography (HPLC). The conclusion based on the experiments are as: (1) The highest experimental solubility was 0.303 mcg/mL RBO at T= 60°C, P= 90 atm, t= 30 min; (2) Solubility of ϒ-oryzanol was influenced by pressure and temperature. As the pressure and temperature increase, the solubility increases; (3) The solubility data of supercritical extraction can be successfully determined using phase equilibrium theory. Meanwhile, tocopherol was found and slightly investigated in this work.

Keywords: rice bran, solubility, supercritical CO2, ϒ-orizanol

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Authors: Shaode Yu, Jiajian Meng, Bing Zhu, Hang Yu, Qiurui Sun

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Speech emotion recognition (SER) is for recognizing human subjective emotions through audio data in-depth analysis. From speech audios, how to comprehensively extract emotional information and how to effectively fuse extracted features remain challenging. This paper presents a dual-stream SER framework that embraces both full training and transfer learning of different networks for thorough feature encoding. Besides, a plug-and-play cross-attention fusion (CAF) module is implemented for the valid integration of the dual-stream encoder output. The effectiveness of the proposed CAF module is compared to the other three fusion modules (feature summation, feature concatenation, and feature-wise linear modulation) on two databases (RAVDESS and IEMO-CAP) using different dual-stream encoders (full training network, DPCNN or TextRCNN; transfer learning network, HuBERT or Wav2Vec2). Experimental results suggest that the CAF module can effectively reconcile conflicts between features from different encoders and outperform the other three feature fusion modules on the SER task. In the future, the plug-and-play CAF module can be extended for multi-branch feature fusion, and the dual-stream SER framework can be widened for multi-stream data representation to improve the recognition performance and generalization capacity.

Keywords: speech emotion recognition, cross-attention fusion, dual-stream, pre-trained

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Authors: Sandhya Devi A

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The protein content of the cranberry squash (protein: 0g) may be increased by extracting protein from the lentils (9 g), which is particularly linked to a lower risk of developing heart disease. Using the technique of alkaline extraction from the lentils flour, protein may be extracted. Alkaline extraction of protein from lentil flour was optimized utilizing response surface approach in order to maximize both protein content and yield. Cranberry squash may be taken if a protein fortification syrup is prepared and processed into the squash.

Keywords: alkaline extraction, cranberry squash, protein fortification, response surface methodology

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Authors: Zuoji Huang, Haiming Qian, Chunlin Wang, Jinyan Sun, Nan Xu

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In this paper, the strategy to extract double road edge lines from acquired road stripe image was explored. The workflow is as follows: the road stripes are acquired by probabilistic boosting tree algorithm and morphological algorithm immediately, and road centerlines are detected by thinning algorithm, so the initial road edge lines can be acquired along the road centerlines. Then we refine the results with big variation of local curvature of centerlines. Specifically, the energy function of edge line is constructed by gradient feature and spectral information, and Dijkstra algorithm is used to optimize the initial road edge lines. The Snake model is constructed to solve the fracture problem of intersection, and the discrete dynamic programming algorithm is used to solve the model. After that, we could get the final road network. Experiment results show that the strategy proposed in this paper can be used to extract the continuous and smooth road edge lines from high-resolution remote sensing images with an accuracy of 88% in our study area.

Keywords: road edge lines extraction, energy function, intersection fracture, Snake model

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Authors: Issa Qabaja, Fadi Thabtah

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Email phishing classification is one of the vital problems in the online security research domain that have attracted several scholars due to its impact on the users payments performed daily online. One aspect to reach a good performance by the detection algorithms in the email phishing problem is to identify the minimal set of features that significantly have an impact on raising the phishing detection rate. This paper investigate three known feature selection methods named Information Gain (IG), Chi-square and Correlation Features Set (CFS) on the email phishing problem to separate high influential features from low influential ones in phishing detection. We measure the degree of influentially by applying four data mining algorithms on a large set of features. We compare the accuracy of these algorithms on the complete features set before feature selection has been applied and after feature selection has been applied. After conducting experiments, the results show 12 common significant features have been chosen among the considered features by the feature selection methods. Further, the average detection accuracy derived by the data mining algorithms on the reduced 12-features set was very slight affected when compared with the one derived from the 47-features set.

Keywords: data mining, email classification, phishing, online security

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Authors: J. K. Alhassan, C. S. Actsu

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This study is on the prediction of feature performance of undergraduate students with Artificial Neural Networks (ANN). With the growing decline in the quality academic performance of undergraduate students, it has become essential to predict the students’ feature academic performance early in their courses of first and second years and to take the necessary precautions using such prediction-based information. The feed forward multilayer neural network model was used to train and develop a network and the test carried out with some of the input variables. A result of 80% accuracy was obtained from the test which was carried out, with an average error of 0.009781.

Keywords: academic performance, artificial neural network, prediction, students

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Authors: I. Berger, N. Machour, F. Portet-Koltalo

Abstract:

Polycyclic aromatic hydrocarbons (PAHs) are toxic and carcinogenic pollutants produced in majority by incomplete combustion processes in industrialized and urbanized areas. After being emitted in atmosphere, these persistent contaminants are deposited to soils or sediments. Even if persistent, some can be partially degraded (photodegradation, biodegradation, chemical oxidation) and they lead to oxygenated metabolites (oxy-PAHs) which can be more toxic than their parent PAH. Oxy-PAHs are less measured than PAHs in sediments and this study aims to compare different analytical tools in order to extract and quantify a mixture of four hydroxylated PAHs (OH-PAHs) and four carbonyl PAHs (quinones) in sediments. Methodologies: Two analytical systems – HPLC with on-line UV and fluorescence detectors (HPLC-UV-FLD) and GC coupled to a mass spectrometer (GC-MS) – were compared to separate and quantify oxy-PAHs. Microwave assisted extraction (MAE) was optimized to extract oxy-PAHs from sediments. Results: First OH-PAHs and quinones were analyzed in HPLC with on-line UV and fluorimetric detectors. OH-PAHs were detected with the sensitive FLD, but the non-fluorescent quinones were detected with UV. The limits of detection (LOD)s obtained were in the range (2-3)×10-4 mg/L for OH-PAHs and (2-3)×10-3 mg/L for quinones. Second, even if GC-MS is not well adapted to the analysis of the thermodegradable OH-PAHs and quinones without any derivatization step, it was used because of the advantages of the detector in terms of identification and of GC in terms of efficiency. Without derivatization, only two of the four quinones were detected in the range 1-10 mg/L (LODs=0.3-1.2 mg/L) and LODs were neither very satisfying for the four OH-PAHs (0.18-0.6 mg/L). So two derivatization processes were optimized, comparing to literature: one for silylation of OH-PAHs, one for acetylation of quinones. Silylation using BSTFA/TCMS 99/1 was enhanced using a mixture of catalyst solvents (pyridine/ethyle acetate) and finding the appropriate reaction duration (5-60 minutes). Acetylation was optimized at different steps of the process, including the initial volume of compounds to derivatize, the added amounts of Zn (0.1-0.25 g), the nature of the derivatization product (acetic anhydride, heptafluorobutyric acid…) and the liquid/liquid extraction at the end of the process. After derivatization, LODs were decreased by a factor 3 for OH-PAHs and by a factor 4 for quinones, all the quinones being now detected. Thereafter, quinones and OH-PAHs were extracted from spiked sediments using microwave assisted extraction (MAE) followed by GC-MS analysis. Several mixtures of solvents of different volumes (10-25 mL) and using different extraction temperatures (80-120°C) were tested to obtain the best recovery yields. Satisfactory recoveries could be obtained for quinones (70-96%) and for OH-PAHs (70-104%). Temperature was a critical factor which had to be controlled to avoid oxy-PAHs degradation during the MAE extraction process. Conclusion: Even if MAE-GC-MS was satisfactory to analyze these oxy-PAHs, MAE optimization has to be carried on to obtain a most appropriate extraction solvent mixture, allowing a direct injection in the HPLC-UV-FLD system, which is more sensitive than GC-MS and does not necessitate a previous long derivatization step.

Keywords: derivatizations for GC-MS, microwave assisted extraction, on-line HPLC-UV-FLD, oxygenated PAHs, polluted sediments

Procedia PDF Downloads 264

Authors: Elif Tugce Aksun Tumerkan, Umran Cansu, Gokhan Boran, Fatih Ozogul

Abstract:

Gelatin is a mixture of peptides obtained from collagen by partial thermal hydrolysis. It is an important and useful biopolymer that is used in the food, pharmacy, and photography products. Generally, gelatins are sourced from pig skin and bones, beef bone and hide, but within the last decade, using alternative gelatin resources has attracted some interest. In this study, functional properties of gelatin extracted from seafood and poultry by-products were evaluated. For this purpose, skins of skipjack tuna (Katsuwonus pelamis) and frog (Rana esculata) were used as seafood by-products and chicken skin as poultry by-product as raw material for gelatin extraction. Following the extraction of gelatin, all samples were lyophilized and stored in plastic bags at room temperature. For comparing gelatins obtained; chemical composition, common quality parameters including bloom value, gel strength, and viscosity in addition to some others like melting and gelling temperatures, hydroxyproline content, and colorimetric parameters were determined. The results showed that the highest protein content obtained in frog gelatin with 90.1% and the highest hydroxyproline content was in chicken gelatin with 7.6% value. Frog gelatin showed a significantly higher (P < 0.05) melting point (42.7°C) compared to that of fish (29.7°C) and chicken (29.7°C) gelatins. The bloom value of gelatin from frog skin was found higher (363 g) than chicken and fish gelatins (352 and 336 g, respectively) (P < 0.05). While fish gelatin had higher lightness (L*) value (92.64) compared to chicken and frog gelatins, redness/greenness (a*) value was significantly higher in frog skin gelatin. Based on the results obtained, it can be concluded that skins of different animals with high commercial value may be utilized as alternative sources to produce gelatin with high yield and desirable functional properties. Functional and quality analysis of gelatin from frog, chicken, and tuna skin showed by-product of poultry and seafood can be used as an alternative gelatine source to mammalian gelatine. The functional properties, including bloom strength, melting points, and viscosity of gelatin from frog skin were more admirable than that of the chicken and tuna skin. Among gelatin groups, significant characteristic differences such as gel strength and physicochemical properties were observed based on not only raw material but also the extraction method.

Keywords: chicken skin, fish skin, food industry, frog skin, gel strength

Procedia PDF Downloads 137